Wireless micropower instrumentation for multimodal acquisition of electrical and chemical neural activity

Development of a Smart Wireless Multisensor Platform for an Optogenetic Brain Implant

Implantable cell replacement therapies promise to completely restore the function of neural structures, possibly changing how we currently perceive the onset of neurodegenerative diseases. One of the major clinical hurdles for the routine implementation of stem cell therapies is poor cell retention and survival, demanding the need to better understand these mechanisms while providing precise and scalable approaches to monitor these cell-based therapies in both pre-clinical and clinical scenarios. This poses significant multidisciplinary challenges regarding planning, defining the methodology and requirements, prototyping and different stages of testing. Aiming toward an optogenetic neural stem cell implant controlled by a smart wireless electronic frontend, we show how an iterative development methodology coupled with a modular design philosophy can mitigate some of these challenges. In this study, we present a miniaturized, wireless-controlled, modular multisensor platform with fully interfaced electronics featuring three different modules: an impedance analyzer, a potentiostat and an optical stimulator. We show the application of the platform for electrical impedance spectroscopy-based cell monitoring, optical stimulation to induce dopamine release from optogenetically modified neurons and a potentiostat for cyclic voltammetry and amperometric detection of dopamine release. The multisensor platform is designed to be used as an opto-electric headstage for future in vivo animal experiments.

A 26.5 pArms Neurotransmitter Front-End With Class-AB Background Subtraction

This paper presents an analog front-end (AFE) for fast-scan cyclic voltammetry (FSCV) with analog background subtraction using a pseudo-differential sensing scheme to cancel the large non-faradaic current before seeing the front-end. As a result, the AFE can be compact and low-power compared to conventional FSCV AFEs with dedicated digital back-ends to digitize and subtract the background from subsequent recordings. The reported AFE, fabricated in a 0.18- μ m CMOS process, consists of a class-AB common-mode rejection circuit, a low-input-impedance current conveyor, and a 1^st-order current-mode delta-sigma (ΔΣ) modulator with an infinite impulse response quantizer. This AFE achieves an effective dynamic range of 83 dB with a state-of-the-art 39.2 pA_rms input-referred noise when loaded with a 1 nF input capacitance (26.5 pA_rms open-circuit) across a 5 kHz bandwidth while consuming an average power of 3.7 μW. This design was tested with carbon-fiber microelectrodes scanned at 300 V/s using flow-injection of dopamine, a key neurotransmitter.

Signal Generation, Acquisition, and Processing in Brain Machine Interfaces: A Unified Review

Brain machine interfaces (BMIs), or brain computer interfaces (BCIs), are devices that act as a medium for communications between the brain and the computer. It is an emerging field with numerous applications in domains of prosthetic devices, robotics, communication technology, gaming, education, and security. It is noted in such a multidisciplinary field, many reviews have surveyed on various focused subfields of interest, such as neural signaling, microelectrode fabrication, and signal classification algorithms. A unified review is lacking to cover and link all the relevant areas in this field. Herein, this review intends to connect on the relevant areas that circumscribe BMIs to present a unified script that may help enhance our understanding of BMIs. Specifically, this article discusses signal generation within the cortex, signal acquisition using invasive, non-invasive, or hybrid techniques, and the signal processing domain. The latest development is surveyed in this field, particularly in the last decade, with discussions regarding the challenges and possible solutions to allow swift disruption of BMI products in the commercial market.

Low-Cutoff Frequency Reduction in Neural Amplifiers: Analysis and Implementation in CMOS 65 nm

Scaling down technology demotes the parameters of AC-coupled neural amplifiers, such as increasing the low-cutoff frequency due to the short-channel effects. To improve the low-cutoff frequency, one solution is to increase the feedback capacitors' value. This solution is not desirable, as the input capacitors have to be increased to maintain the same gain, which increases the area and decreases the input impedance of the neural amplifier. We analytically analyze the small-signal behavior of the neural amplifier and prove that the main reason for the increase of the low-cutoff frequency in advanced CMOS technologies is the reduction of the input resistance of the operational transconductance amplifier (OTA). We also show that the reduction of the input resistance of the OTA is due to the increase in the gate oxide leakage in the input transistors. In this paper, we explore this fact and propose two solutions to reduce the low-cutoff frequency without increasing the value of the feedback capacitor. The first solution is performed by only simulation and is called cross-coupled positive feedback that uses pseudoresistors to provide a negative resistance to increase the input resistance of the OTA. As an advantage, only standard CMOS transistors are used in this method. Simulation results show that a low-cutoff frequency of 1.5 Hz is achieved while the midband gain is 30.4 dB at 1 V. In addition, the power consumption is 0.6 μW. In the second method, we utilize thick-oxide MOS transistors in the input differential pair of the OTA. We designed and fabricated the second method in the 65 nm TSMC CMOS process. Measured results are obtained by in vitro recordings on slices of mouse brainstem. The measurement results show that the bandwidth is between 2 Hz and 5.6 kHz. The neural amplifier has 34.3 dB voltage gain in midband and consumes 3.63 μW at 1 V power supply. The measurement results show an input-referred noise of 6.1 μV_rms and occupy 0.04 mm² silicon area.

Multi-Channel Neural Recording Implants: A Review

The recently growing progress in neuroscience research and relevant achievements, as well as advancements in the fabrication process, have increased the demand for neural interfacing systems. Brain-machine interfaces (BMIs) have been revealed to be a promising method for the diagnosis and treatment of neurological disorders and the restoration of sensory and motor function. Neural recording implants, as a part of BMI, are capable of capturing brain signals, and amplifying, digitizing, and transferring them outside of the body with a transmitter. The main challenges of designing such implants are minimizing power consumption and the silicon area. In this paper, multi-channel neural recording implants are surveyed. After presenting various neural-signal features, we investigate main available neural recording circuit and system architectures. The fundamental blocks of available architectures, such as neural amplifiers, analog to digital converters (ADCs) and compression blocks, are explored. We cover the various topologies of neural amplifiers, provide a comparison, and probe their design challenges. To achieve a relatively high SNR at the output of the neural amplifier, noise reduction techniques are discussed. Also, to transfer neural signals outside of the body, they are digitized using data converters, then in most cases, the data compression is applied to mitigate power consumption. We present the various dedicated ADC structures, as well as an overview of main data compression methods.

Hybrid CMOS-Graphene Sensor Array for Subsecond Dopamine Detection

We introduce a hybrid CMOS-graphene sensor array for subsecond measurement of dopamine via fast-scan cyclic voltammetry (FSCV). The prototype chip has four independent CMOS readout channels, fabricated in a 65-nm process. Using planar multilayer graphene as biologically compatible sensing material enables integration of miniaturized sensing electrodes directly above the readout channels. Taking advantage of the chemical specificity of FSCV, we introduce a region of interest technique, which subtracts a large portion of the background current using a programmable low-noise constant current at about the redox potentials. We demonstrate the utility of this feature for enhancing the sensitivity by measuring the sensor response to a known dopamine concentration in vitro at three different scan rates. This strategy further allows us to significantly reduce the dynamic range requirements of the analog-to-digital converter (ADC) without compromising the measurement accuracy. We show that an integrating dual-slope ADC is adequate for digitizing the background-subtracted current. The ADC operates at a sampling frequency of 5-10 kHz and has an effective resolution of about 60 pA, which corresponds to a theoretical dopamine detection limit of about 6 nM. Our hybrid sensing platform offers an effective solution for implementing next-generation FSCV devices that can enable precise recording of dopamine signaling in vivo on a large scale.

Miniaturized FDDA and CMOS Based Potentiostat for Bio-Applications

A novel fully differential difference CMOS potentiostat suitable for neurotransmitter sensing is presented. The described architecture relies on a fully differential difference amplifier (FDDA) circuit to detect a wide range of reduction-oxidation currents, while exhibiting low-power consumption and low-noise operation. This is made possible thanks to the fully differential feature of the FDDA, which allows to increase the source voltage swing without the need for additional dedicated circuitry. The FDDA also reduces the number of amplifiers and passive elements in the potentiostat design, which lowers the overall power consumption and noise. The proposed potentiostat was fabricated in 0.18 µm CMOS, with 1.8 V supply voltage. The device achieved 5 µA sensitivity and 0.99 linearity. The input-referred noise was 6.9 µV rms and the flicker noise was negligible. The total power consumption was under 55 µW. The complete system was assembled on a 20 mm × 20 mm platform that includes the potentiostat chip, the electrode terminals and an instrumentation amplifier for redox current buffering, once converted to a voltage by a series resistor. the chip dimensions were 1 mm × 0.5 mm and the other PCB components were off-chip resistors, capacitors and amplifiers for data acquisition. The system was successfully tested with ferricyanide, a stable electroactive compound, and validated with dopamine, a popular neurotransmitter.

An integrated interface for peripheral neural system recording and stimulation: system design, electrical tests and in-vivo results

The prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of 2 integrated circuits: a standard CMOS device for neural recording and a HVCMOS device for neural stimulation. The integrated circuits have been realized in 2 different 0.35μ m CMOS processes available from ams. The complete system incorporates 8 channels each including the analog front-end, the A/D conversion, based on a sigma delta architecture and a programmable stimulation module implemented as a 5-bit current DAC; two voltage boosters supply the output stimulation stage with a programmable voltage scalable up to 17V. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μ V r m s , and to selectively elicit the tibial and plantar muscles using different active sites of the electrode.

A User-Configurable Headstage for Multimodality Neuromonitoring in Freely Moving Rats

Multimodal monitoring of brain activity, physiology, and neurochemistry is an important approach to gain insight into brain function, modulation, and pathology. With recent progress in micro- and nanotechnology, micro-nano-implants have become important catalysts in advancing brain research. However, to date, only a limited number of brain parameters have been measured simultaneously in awake animals in spite of significant recent progress in sensor technology. Here we have provided a cost and time effective approach to designing a headstage to conduct a multimodality brain monitoring in freely moving animals. To demonstrate this method, we have designed a user-configurable headstage for our micromachined multimodal neural probe. The headstage can reliably record direct-current electrocorticography (DC-ECoG), brain oxygen tension (PbrO₂), cortical temperature, and regional cerebral blood flow (rCBF) simultaneously without significant signal crosstalk or movement artifacts for 72 h. Even in a noisy environment, it can record low-level neural signals with high quality. Moreover, it can easily interface with signal conditioning circuits that have high power consumption and are difficult to miniaturize. To the best of our knowledge, this is the first time where multiple physiological, biochemical, and electrophysiological cerebral variables have been simultaneously recorded from freely moving rats. We anticipate that the developed system will aid in gaining further insight into not only normal cerebral functioning but also pathophysiology of conditions such as epilepsy, stroke, and traumatic brain injury.

Neurochemostat: A Neural Interface SoC With Integrated Chemometrics for Closed-Loop Regulation of Brain Dopamine

This paper presents a 3.3×3.2 mm(2) system-on-chip (SoC) fabricated in AMS 0.35 μm 2P/4M CMOS for closed-loop regulation of brain dopamine. The SoC uniquely integrates neurochemical sensing, on-the-fly chemometrics, and feedback-controlled electrical stimulation to realize a "neurochemostat" by maintaining brain levels of electrically evoked dopamine between two user-set thresholds. The SoC incorporates a 90 μW, custom-designed, digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by 400 V/s fast-scan cyclic voltammetry (FSCV) with a carbon-fiber microelectrode (CFM). Specifically, the DSP unit executes a chemometrics algorithm based upon principal component regression (PCR) to resolve in real time electrically evoked brain dopamine levels from pH change and CFM background-current drift, two common interferents encountered using FSCV with a CFM in vivo. Further, the DSP unit directly links the chemically resolved dopamine levels to the activation of the electrical microstimulator in on-off-keying (OOK) fashion. Measured results from benchtop testing, flow injection analysis (FIA), and biological experiments with an anesthetized rat are presented.

A 200-Channel Area-Power-Efficient Chemical and Electrical Dual-Mode Acquisition IC for the Study of Neurodegenerative Diseases

Microelectrode array (MEA) can be used in the study of neurodegenerative diseases by monitoring the chemical neurotransmitter release and the electrical potential simultaneously at the cellular level. Currently, the MEA technology is migrating to more electrodes and higher electrode density, which raises power and area constraints on the design of acquisition IC. In this paper, we report the design of a 200-channel dual-mode acquisition IC with highly efficient usage of power and area. Under the constraints of target noise and fast settling, the current channel design saves power by including a novel current buffer biased in discrete time (DT) before the TIA (transimpedance amplifier). The 200 channels are sampled at 20 kS/s and quantized by column-wise SAR ADCs. The prototype IC was fabricated in a 0.18 μm CMOS process. Silicon measurements show the current channel has 21.6 pArms noise with cyclic voltammetry (CV) and 0.48 pArms noise with constant amperometry (CA) while consuming 12.1 μW . The voltage channel has 4.07 μVrms noise in the bandwidth of 100 kHz and 0.2% nonlinearity while consuming 9.1 μW. Each channel occupies 0.03 mm(2) area, which is among the smallest.

A CMOS Amperometric System for Multi-Neurotransmitter Detection

In vivo multi-target and selective concentration monitoring of neurotransmitters can help to unravel the brain chemical complex signaling interplay. This paper presents a dedicated integrated potentiostat transducer circuit and its selective electrode interface. A custom 2-electrode time-based potentiostat circuit was fabricated with 0.13 μm CMOS technology and provides a wide dynamic input current range of 20 pA to 600 nA with 56 μ W, for a minimum sampling frequency of 1.25 kHz. A multi-working electrode chip is functionalized with carbon nanotubes (CNT)-based chemical coatings that offer high sensitivity and selectivity towards electroactive dopamine and non-electroactive glutamate. The prototype was experimentally tested with different concentrations levels of both neurotransmitter types, and results were similar to measurements with a commercially available potentiostat. This paper validates the functionality of the proposed biosensor, and demonstrates its potential for the selective detection of a large number of neurochemicals.

An Inductive Power and Data Telemetry Subsystem With Fast Transient Low Dropout Regulator for Biomedical Implants

This paper presents a capacitorless low-dropout (LDO) regulator with fast transient response and data reverse telemetry circuit for fully implantable wireless transmission applications. We propose a novel hybrid feedback structure using high-frequency compensation technology to achieve a rapid transient response for the LDO regulator. To reduce the size of the implant and transmit neural recordings through the same coil without interfering with power transmission, the load-shift-key (LSK) modulation technique is adopted for back data telemetry. The proposed implantable chip, fabricated using commercial 0.18 μm complementary metal oxide semiconductor technology, yielded an output power of 15 mW. Under 1.15 V operation voltage, the maximum overshoot and undershoot voltages were less than 45 mV and 55 mV, respectively, for a 15 mA full-load current whose rising and falling time were less than 100 ns. The proposed LSK transceiver uses a digitized demodulator to improve bandwidth efficiency for low carrier frequency operation.

Wireless Flexible Smart Bandage for Continuous Monitoring of Wound Oxygenation

Current methods in treating chronic wounds have had limited success in large part due to the open loop nature of the treatment. We have created a localized 3D-printed smart wound dressing platform that will allow for real-time data acquisition of oxygen concentration, which is an important indicator of wound healing. This will serve as the first leg of a feedback loop for a fully optimized treatment mechanism tailored to the individual patient. A flexible oxygen sensor was designed and fabricated with high sensitivity and linear current output. With a series of off-the-shelf electronic components including a programmable-gain analog front-end, a microcontroller and wireless radio, an integrated electronic system with data readout and wireless transmission capabilities was assembled in a compact package. Using an elastomeric material, a bandage with exceptional flexibility and tensile strength was 3D-printed. The bandage contains cavities for both the oxygen sensor and the electronic systems, with contacts interfacing the two systems. Our integrated, flexible platform is the first step toward providing a self-operating, highly optimized remote therapy for chronic wounds.

Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

Fully integrated CMOS microsystem for electrochemical measurements on 32 × 32 working electrodes at 90 frames per second

Microelectrode arrays offer the potential to electrochemically monitor concentrations of molecules at high spatial resolution. However, current systems are limited in the number of sensor sites, signal resolution, and throughput. Here, we present a fully integrated complementary metal oxide semiconductor (CMOS) system with an array of 32 × 32 working electrodes to perform electrochemical measurements like amperometry and voltammetry. The array consists of platinum electrodes with a center-to-center distance of 100 μm and electrode diameters of 5 to 50 μm. Currents in the range from 10 μA down to pA can be measured. The current is digitized by sigma-delta converters at a maximum resolution of 13.3 bits. The integrated noise is 220 fA for a bandwidth of 100 Hz, allowing for detection of pA currents. Currents can be continuously acquired at up to 1 kHz bandwidth, or the whole array can be read out rapidly at a frame rate of up to 90 Hz. The results of the electrical characterization meet the requirements of a wide range of electrochemical methods including cyclic voltammograms and amperometric images of high spatial and temporal resolution.

A highly linear fully integrated powerline filter for biopotential acquisition systems

Powerline interference is one of the most dominant problems in detection and processing of biopotential signals. This work presents a new fully integrated notch filter exhibiting high linearity and low power consumption. High filter linearity is preserved utilizing active-RC approach while IC implementation is achieved through replacing passive resistors by R-2R ladders achieving area saving of approximately 120 times. The filter design is optimized for low power operation using an efficient circuit topology and an ultra-low power operational amplifier. Fully differential implementation of the proposed filter shows notch depth of 43 dB (78 dB for 4th-order) with THD of better than -70 dB while consuming about 150 nW from 1.5 V supply.

An experimental setup to characterize MR switched gradient-induced potentials

We have developed an experimental setup as an in vitro research tool for studying the contamination of electrophysiological signals (EPS) by MRI environment; particularly, when due to the switched gradient-induced potentials. The system is composed of: 1) a MRI compatible module for the transmission of the EPS into the MRI tunnel, 2) a gelatin-based tissue-mimicking phantom, placed inside the tunnel, in which EPS is injected, 3) a detection module composed of a five input channel MRI compatible transmitter placed inside the tunnel, allowing an on-site pre-amplification of the bio-potentials and their transmission, via an optical fiber cable, to a four filtered output per channel receiver (350 Hz, 160 Hz, 80 Hz, and 40 Hz, for a total of 20 channels) placed in the control room, and 4) a signal processing algorithm used to analyze the generated induced potentials. A set of tests were performed to validate the electronic performances of the setup. We also present in this work an interesting application of the setup, i.e., the acquisition and analysis of the induced potentials with respect of the slice orientation for a given MRI sequence. Significant modifications of the time and frequency characteristics were observed with respect to axial, coronal or sagittal orientations.

A 0.09 μW low power front-end biopotential amplifier for biosignal recording

This work presents a biopotential front-end amplifier in which the MOS transistors are biased in subthreshold region with a supply voltage and current of 0.4-0.8 V and 0.23-1.86 μA, respectively, to reduce the system power. Flicker noise is then removed using a chopping technique, and differential interference produced by electrode impedance imbalance is suppressed using a Gm-C filter. Additionally, the circuit is fabricated using TSMC 0.18 μm CMOS technology with a core area of 0.77 × 0.36 mm². With a minimum supply voltage of 0.4 V, the measured SNR and power consumption of the proposed IC chip are 54.1 dB and 0.09μW, respectively.

Recent advances in neural recording microsystems

The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

A VLSI Neural Monitoring System With Ultra-Wideband Telemetry for Awake Behaving Subjects

Long-term monitoring of neuronal activity in awake behaving subjects can provide fundamental information about brain dynamics for neuroscience and neuroengineering applications. Here, we present a miniature, lightweight, and low-power recording system for monitoring neural activity in awake behaving animals. The system integrates two custom designed very-large-scale integrated chips, a neural interface module fabricated in 0.5 μm complementary metal-oxide semiconductor technology and an ultra-wideband transmitter module fabricated in a 0.5 μm silicon-on-sapphire (SOS) technology. The system amplifies, filters, digitizes, and transmits 16 channels of neural data at a rate of 1 Mb/s. The entire system, which includes the VLSI circuits, a digital interface board, a battery, and a custom housing, is small and lightweight (24 g) and, thus, can be chronically mounted on small animals. The system consumes 4.8 mA and records continuously for up to 40 h powered by a 3.7-V, 200-mAh rechargeable lithium-ion battery. Experimental benchtop characterizations as well as in vivo multichannel neural recordings from awake behaving rats are presented here.

A miniaturized device for wireless FSCV monitoring of dopamine in an ambulatory subject

This paper reports on a miniaturized device for wireless monitoring of extracellular dopamine levels in the brain of an ambulatory rat using fast-scan cyclic voltammetry at a carbon-fiber microelectrode. The device comprises integrated circuitry for neurochemical recording fabricated in 0.5-microm double-poly triple-metal CMOS technology, which is assembled and packaged on a miniature rigid-flex substrate together with a few external components for supply generation, biasing, and chip programming. The device operates from a single 3-V battery, weighs 2.3 g (including the battery), and upon implantation successfully captures the effects of the psychostimulant amphetamine on electrically and non-electrically evoked dopamine neurotransmission in the caudateputamen region of an ambulatory rat's forebrain.